Intelligent Reflecting Surface Enhanced Millimeter-Wave NOMA Systems

TL;DR

This paper proposes an IRS-enhanced mmWave NOMA system with a novel joint optimization algorithm that significantly improves sum-rate performance, demonstrating the effectiveness of IRS and discrete phase shifts in such systems.

Contribution

It introduces a joint optimization framework for active and passive beamforming and power allocation in IRS-enhanced mmWave NOMA systems, with an iterative algorithm handling non-convexity.

Findings

Significant sum-rate gains with the proposed scheme.

Discrete phase shifts nearly match continuous phase shift performance.

The algorithm effectively optimizes beamforming and power allocation.

Abstract

In this paper, a downlink intelligent reflecting surface (IRS) enhanced millimeter-wave (mmWave) non-orthogonal multiple access (NOMA) system is considered. A joint optimization problem over active beamforming, passive beamforming and power allocation is formulated. Due to the highly coupled variables, the formulated optimization problem is non-convex. To solve this problem, an alternative optimization and successive convex approximation based iterative algorithm is proposed. Numerical results illustrate that: 1) the proposed scheme offers significant sum-rate gains, which confirms the effectiveness of introducing IRS for mmWave-NOMA systems; 2) the proposed algorithm with discrete phase shifts can achieve close performance to that of continuous phase shifts.